KR20170002506A - Method for determining the parameters of an ic manufacturing process by a differential procedure - Google Patents

Abstract

A method for determining parameters of an IC manufacturing process by a difference procedure. The present invention discloses a method for easily determining parameters of a second manufacturing process from parameters of a first process. A metric representing the difference between the two processes is calculated from the plurality of parameter values, which can be measured for two processes on the calibration layout or can be determined from the existing values for the layout or reference data for the two processes by interpolation / have. The number of metrics is selected and these combinations provide a precise representation of the differences between the two processes in all design areas. Preferably, the metric is calculated as a convolution of the target design and a composite of the kernel function and the deformation function.

Description

METHOD FOR DETERMINING THE PARAMETERS OF AN IC MANUFACTURING PROCESS BY A DIFFERENTIAL PROCEDURE BACKGROUND OF THE INVENTION [0001]

The invention applies to the field of electronic or optical lithography. The present invention is applied to mask writing and direct writing among other processes. The present invention can also be applied to other stages of the semiconductor manufacturing process, such as nanoimprint, Directed Self Assembly (DSA), etching, CMP (Chemincal Mechanical Polishing / Planarization), annealing, baking,

During the process of mask writing or direct writing, several factors cause errors and prevent the achievement of the expected resolution. Some of these factors are electron scattering (front and back scattering), resist diffusion, resist thickness, etching, flame, fogging, measurement and the like. Several strategies exist to improve the resolution and reduce the effects of these phenomena, such as proximity effect correction (PEC), fogging effect correction (FEC), and etching compensation do. The strategy is based on the prediction of the effect of each of the effects of their correction using dose and / or geometry compensation. Therefore, the quality of the calibration depends on the quality of the model used to predict the phenomenon, and the model is different for each manufacturing process. The high accuracy of the model and calibration can be reliably obtained, but with high computational costs.

The problem is that, in any production flow, it is sometimes necessary to change the process. This may be due to the purchase of new equipment, new resists, and so on. In many cases, it may be desirable to maintain the same behavior as from the previous flow. In the prior art, this is accomplished by tuning the process state. Time-consuming and quite expensive physical process parameters (etch bias, power, resist thickness, baking, etc.) are changed.

A solution to reduce this burden was found in the context of optical proximity correction (OPC). Some of these solutions are disclosed by U.S. Patent Nos. 6,033,814 and 6,463,403. The basic idea of these methods in the conventional way is to calibrate the model for two separate models, namely the existing process and the new process, and the output of the model for the new process to the output of the model of the existing process It should be matched. Once the two calibrations are performed, it is necessary to use the two calibrated models to change the target of the existing process to the target of the new process. Multiple calculation procedures (two calibrations, one simulation and one calibration) have to be performed, which is quite burdensome and computationally heavy.

The present invention mitigates burden and computing workload by implementing a single difference model in which one process imitates another process and reduces calibration and correction effects. In addition, the use of a process matching method may limit the matching process when the used measurement point is not spread over the entire design, for example, to maintain the matching result, to perform either extrapolation and interpolation between measurements, By applying the precedence for, we can obtain the desired result more flexibly.

To this end, the invention discloses, by a computer, a method for determining an output vector comprising an output variable, the output vector defining a correction to be applied to a feature of a second process for manufacturing a semiconductor integrated circuit, The method includes: computer code instructions for obtaining a first series of values of an input vector for a first process for fabricating the same semiconductor integrated circuit at a first plurality of points of a first layout; Computer code instructions for obtaining a second set of values of a component of an input vector for a second process at one of a first plurality of points on a first layout and a second plurality of points on a second layout; A computer code instruction for determining a value of a state vector comprising a state variable; the state vector representing a state of a difference between a first series of values of the input vector and a second series of values; Computer code instructions for obtaining an output vector for a series of values of a state vector, by direct computation.

Preferably, the first step is a virtual process, and the virtual process produces the same output layout as the input layout.

Preferably, the output vector is at least one of an output variable, an edge displacement, a dose modulation and a combination thereof.

Preferably, the input vector comprises at least one of a CD and a space of an input design of the integrated circuit as an input variable.

Preferably, the first layout is a calibration layout.

Preferably, the first process is a reference process.

Preferably, a series of values of the state vector at the output of at least one of the interpolation procedure and the extrapolation procedure is calculated using the first and second series of values of the input vector.

Preferably, the first state variable is selected based on the discriminative power of the components of the parameter vector on the region of the values for which the first and second processes are to be used.

Preferably, a second state variable is added to the first state variable to increase the combined discrimination power within the specified calculated load budget.

Preferably, the state vector comprises a state variable representing at least one of CD, space and density.

Preferably, determining a circle in the interior while touching a first edge of a portion of the design, determining a surface area of a portion of the circle included between the first edge of the portion of the design and the second edge of the portion of the design And calculating a state variable representing the CD, as a ratio of the surface area of a part of the circle to the surface area of the circle, the state variable representing the CD is calculated.

Preferably, the edge of the first part of the design facing the next second part of the design is contacted and the circle on the outside is determined, and the circle of the circle to be included between the edge of the first part of the design and the edge of the second part of the design A state variable representing a space is calculated by calculating a state variable indicating a space, as a ratio of the surface area of a portion of the disk to the surface area of the disk, which determines the surface area of the portion.

Preferably, a circle covering the plurality of parts of the design is determined, a surface area of a part of the circle included in a part of the design is determined, and a state variable indicating a long distance density as a ratio of the surface area of a part of the circle to the surface area of the circle The state variable indicating the long-distance density is calculated.

Preferably, the state vector comprises a state variable indicating at least one of an outer density and an inner density.

Preferably, the external density is calculated by multiplying the convolution of the synthesis of the kernel function centered on the point of interest and the point of interest of the target design and the deformation function according to the viewing angle and the selected angle of departure, The angle of deviation is selected so as to see the outside of the screen.

Preferably, the internal density is calculated by the product of the convolution of the synthesis of the kernel function centered at the point of interest and the point of interest of the target design and the deformation function according to the viewing angle and the selected angle of departure, The angle of deviation is selected so as to observe the inside of the lens.

Preferably, the output variable is an edge displacement that is converted to a dose modulation using a transform function.

Advantageously, said conversion function is one of a hat function, a rectangular function, a triangular function and a Gaussian function.

Advantageously, said conversion function is a hat function defined by a parameter W _h .

Preferably, the parameter W _h is determined such that W _h ≥ Max (abs (ΔEdge)) and W _h ≤ minShapeDistance, where ΔEdge is an edge obtained from a first series of values and a second series of values ) Values, and the ShapeDistance is measured on the target layout.

Preferably, the value Th of the percentage of the resist threshold is calculated using the formula Th = 0.5-DeltaEdge / Wh.

The invention also discloses a computer program for determining a series of corrections to be applied to a second parameter of a second process for producing a semiconductor integrated circuit, Computer code instructions for obtaining a first series of values of an input vector for a first process for fabricating the same semiconductor integrated circuit; Computer code instructions for obtaining a second set of values of a component of an input vector for a second process at one of a first plurality of points on a first layout and a second plurality of points on a second layout; A computer code instruction for determining a value of a state vector comprising a state variable; the state vector representing a state of a difference between a first series of values of the input vector and a second series of values; Computer code instructions for obtaining an output vector for a series of values of a state vector, by direct computation.

The present invention also relates to a semiconductor manufacturing equipment configured to use the output of a computer program according to claim 21, wherein the semiconductor manufacturing equipment is directly written onto a semiconductor wafer, written onto a mask plate, etched, chemically or mechanically planarized, Annealing, and inspection of the mask or semiconductor surface.

Another advantage of the present invention is that only a plurality of measurements having respective exposure conditions are required to perform matching. Yet another advantage of the present invention is that it is possible to match two processes while handling one or both of them as a black box. This is useful when one mask manufacturer wants to build the same mask that is provided by another mask manufacturer that will not have access to the interior of the process. Another advantage is that matching the second process to the first process produces data that can be used to perform the backmatching (the first process to the second process). Another advantage is that when the calibration step is performed prior to the process matching step, a variety of options are available depending on the compromise between accuracy and cost: a single calibration layout in which both processes are applied to collect the measurement results from both sources , Utilizing the results of two different calibration layouts, and using the measurements performed on the actual design targets from the source and target processes.

It is an advantage of the present invention that there is no need to necessarily use the functional models of the various process steps that need to be reversed to produce a simulation result that must be matched to the tolerance criteria before being input to the calibration step of the lithography process.

In some embodiments of the present invention, the geometric correction to be applied to the input layout can be defined directly (i.e., without any model reversal) by considering the ideal reference process: the ideal process is the process of generating the same target layout as the input layout . The method of the present invention can create a target layout by directly generating a correction to be applied to the geometry of the input layout.

BRIEF DESCRIPTION OF THE DRAWINGS The present invention and its various features and advantages will become better understood and appreciated by referring to the various embodiments and the following drawings.
1 shows a flow chart of a method of matching a second process to a first process in the prior art.
Figure 2 shows a flow diagram of a process matching method using a calibration layout in accordance with multiple embodiments of the present invention.
Figure 3 shows a flow diagram of a process matching method using two different layouts and interpolation / extrapolation in multiple embodiments of the present invention.
4 shows a flow diagram of a process matching method and an interpolation / extrapolation method using two reference input data sets in a plurality of embodiments of the present invention.
Figure 5 illustrates an interpolation / extrapolation method in multiple embodiments of the present invention.
Figures 6 and 7 show two flow charts of a variant of the invention.
Figure 8 shows three different layouts with measurement points.
Figures 9a, 9b and 9c illustrate the use of space metric / state variables with the layout of Figure 8.
Figures 10a, 10b and 10c illustrate the use of CD metric / state variables with the layout of Figure 8;
Figs. 11A, 11B and 11C illustrate the use of density metric / state variables with the layout of Fig.

Figure 1 shows a flow diagram of a method for matching a second process according to the prior art to a first process.

In the prior art shown by the two US patents cited, there are two calibration steps, a first calibration 110 for the process in use (process I), and a second calibration 120 for the new process (process II) . Then, a layout re-targeting step 130 is performed so that a layout corresponding to the layout in which the process II is produced by the process I can be generated. Thus, this prior art process involves three complex steps. This is one of the reasons why the method of the present invention is preferable.

Figure 2 shows a flow diagram of a process matching method using a calibration layout in accordance with multiple embodiments of the present invention.

The strategy includes using measurements from both processes and then calibrating the difference model so that one process can mimic another process. In this approach, no other information is required from the matched process other than the measurement results. This approach also offers the advantage that both processes can be matched together using a single model without any additional effort.

The first step 210 is to define a calibration layout that the process 220, 230 to be matched can vary according to the major features of the design in use. For example, if a process for reproducing a Manhattan design with dense lines is used predominantly, it would be desirable for the calibration layout to include dense lines. Likewise, the process can be used for dense or scattered freeform designs. Optionally, it is not necessary to form a calibration layout. It is possible to use simulations for the two processes to be matched against the measurement results or the target design.

A key step 240 of the method of the present invention is to calibrate the difference model for the results 250, 260 of the two processes 220, 230.

The final model may then be applied to the calibration flow 270 using different types of process matching strategies. For example, a combination of dose and geometry modulation may be applied, as disclosed in commonly owned European Patent Application No. 2559054, the present invention. In addition, a combination correction process of dose and geometry modulation, as disclosed in French Patent Application No. 10/52862, can be applied to the target design.

The difference model correction step 240 will be described in more detail.

Processes for fabricating semiconductor ICs are characterized by a plurality of variables that can vary in importance depending on the type of manufacturing stage and target design. When modeling the process effect, some parameters, such as CD (Critical Dimension), space, edge, density, etc., will be selected in the space area. Some other variables will be selected in the electron beam dose region (e.g., resist threshold). The roughness of the contour can also be used, especially when the free-form design is within the field of use of the process.

It may also be desirable to express the output variable as a function of the vector. This vector has a variable to be used as a component so that the difference between the processes through the field of use can be well expressed. Some of the variables will define the state of the model (eg CD, space, density). These variables may be referred to as "state variables" or metrics and will define "state vectors ". Some others will define the difference output of the model (edge displacement, dose variation, combination of both, etc.). These variables will be referred to as "output variables" and will form "output vectors ".

Preferably, the difference model can be calibrated from measurements on a calibration layout that can be grouped into "input vectors" and "input variables". The input variables may be CD, space or other parameters such as contour roughness (i.e., Line Edge Roughness (LER) or Line Width Roughness (LWR)), or Line End Shortening (LES), corner rounding, and the like. Measurements should be made at a sufficient number of points to cover the area of use and the point location should also indicate the diversity of the sub-layout. However, the present invention can be performed without using a large and expensive calibration layout step.

When using the calibration layout, a first series of values of the input vector 250 is measured at a plurality of measurement points by applying process I 220, and process II 230 is applied to calculate the value of the value of the parameter 260 2 series is measured. Generally, the number of measurement points is about 1000.

According to the present invention, it is desirable to define a state variable, or "metric ", that is selected through the field of use so as to possibly indicate the state of the difference of the input variables of the two processes. Preferably, the metric will also be represented as a vector. The state vector may be determined by selecting a first component (e.g., CD), testing the model, adding a second component, a third component (e.g., space and density), etc., Can be experimentally configured by interrupting the process.

An example of a metric is provided in the following description of Figures 8-11.

The output vector determined by the differential model of the present invention is then applied to the data preparation file of Process I to derive the data preparation file of Process II (step 270).

In some cases, it may be desirable to use a variable in the dose region in the correction algorithm. In this case, it is preferable to use a conversion function that can be applied to the variable of the space area. However, dose or dose variations can be directly selected as output variables.

This conversion function may be the simplest option, the hat function. However, other options are available: rectangle functions, triangle functions, or Gaussian functions. It is necessary to calculate the dose function that is formed at finite intervals when the transformation function is combined with the space function that forms the target parameters (edge displacement, size, etc.). Therefore, the transform function must be integrable (by finite integration in the positive space) and monotonous by half-space. It may be desirable to use a symmetric transform function.

 An example of an embodiment of such a transformation using a hat function is provided as follows.

The width Wh of the hat is calculated on the basis of the characteristics of the target layout and the difference in Critical Dimension (CD) or edge at measurement points MP _i1 and MP _i2 .

The first condition to be fulfilled is that the width of the hat function must be large enough to represent all edge position differences between the two processes. Thus, at the measurement point, considering CD _Process2 - CD _Process1 = ΔCD = ΔEdge, the width W _h of the hat function should satisfy the first inequality:

W _h ? Max (abs (? E dge)) (1)

Here, Max is the maximum value of the measurement at MP _i , and the number and position of the measurement points can be carefully selected to provide a representative value.

In addition, the width of the hat function must be small enough to prevent the two patterns from interacting. Thus, the width W _h of the hat function must also satisfy the second inequality:

W _h ? Min (ShapeDistance) (2)

Where ShapeDistance is the distance between adjacent patterns in the target layout.

Therefore, the hat function can be used as a PSF in the model only when the above two conditions can be satisfied at the same time, which means:

max (abs (DeltaEdge)) min (Space) (3)

Unless this condition can be satisfied, different conversion functions should be attempted.

The threshold for any pattern with a difference of zero should not be changed. In this case, it should be kept at 0.5. Any difference as shown below should be converted to a threshold change:

Th = 0.5 -? E dge / W _h (4)

The value of the threshold of the matched process can be determined from the difference of the edge values at the plurality of measurement points MP _i for each pattern, as will be described in the following numerical examples.

Consider that the aim is to match Step 2 to Step 1. This means that it is expected to perform the exposure using the process 1 and obtain the same result to be obtained by using the process 2. The calculation can also be performed in the opposite direction. A set of targets / measurements can be considered.

Table 1

The first step is to compute the difference (ΔCD, ΔEdge) between CD and edge between process 1 and process 2. The objective is to obtain the edge placement difference ΔEdge. Based on the values of columns (D) and (E) in Table 1, it is simple to calculate? CD and? Edge at the selected measuring point.

W _h ? Max (abs (? Edge)) = 5 nm

The maximum value is given by:

W _h ? Min (space) = 60 nm

Thus, the width of the hat function may be any value between 5 nm and 60 nm. In this example, we arbitrarily set the value at 20 nm, but any value that performs the constraints of equations (1) and (2) will also be used.

The second step is to convert each change in CD (nm) into a percentage change in threshold (μC / cm 2). This is performed based on Equation (3) applied to the value of column (F) in Table 2 below, which is the difference between the values of column (D) and column (E)

Th = 0.5 -? E dge / W _h = 0.5 -? E dge / 20

Table 2

Therefore, the conversion between the parameter of the space area and the parameter of the dose area is obtained.

Figure 3 shows a flow diagram of a process matching method using two different layouts and interpolation / extrapolation in multiple embodiments of the present invention.

The use of calibration layouts can be cumbersome and expensive. Instead, in a variation of the present invention, it may be desirable to utilize existing measurement results 330, 340 obtained from two different layouts 310 and 320.

A step 350 is then performed to calculate the result of one of the measurement results of one of the layouts 340 or 330 in the set of measurement points of the other layout 330 or 340. Preferably, this step is a combination of interpolation and extrapolation. This interpolation / extrapolation step may be linear or use different functions selected to account for layout differences. This step can introduce and correct artifacts that will reduce the precision of matching. For example, different size factors may be applied as corrections depending on the size of the sub-portion of the design. Alternatively, an interpolation / extrapolation step may be applied to the state vector.

Thereafter, as described above, step 360 of the difference model correction is applied, including the use of a metric vector.

Thereafter, as described above, the correction step 370 of the data preparation file of the process I is applied to obtain the parameters of the process II.

One of the advantages of the variant of FIG. 3 is that it allows calibration of the differential model without having to access the trust data for the two processes to be matched.

4 shows a flow diagram of a process matching method and an interpolation / extrapolation method using two reference input data sets in a plurality of embodiments of the present invention.

The embodiment of Fig. 4 is not much different from the embodiment of Fig. 3, except that instead of layout, the method uses data from two processes to be matched which may not be the measurement result. For example, the input data may be a set of data that is simulated from an already existing model. This may be a linearity requirement, for example, the boundary of the CD versus pitch curve.

The interpolation / extrapolation steps between the input data of the process I and the process II are performed instead of the measurement results of two different layouts. A correction step may also be applied.

The difference model calibration step and the design correction step of the previous embodiment are performed in the same manner as described above.

Figure 5 illustrates an interpolation / extrapolation method in multiple embodiments of the present invention.

The parameter measurement of the process I for the first layout or the reference data of this process I for the plurality of points 510, 520, 530 is obtained. The best fit curve (540) of these measurements is calculated using known interpolation / extrapolation methods.

For the second layout, the reference data of this process II is obtained for a measure of the parameters of process II or for a plurality of points 550, 560, 570. The best fit curve (580) of these measurements is calculated using known interpolation / extrapolation methods.

The difference parameter 590 can then be calculated at all measurement points in Process I and Process II. The calibration steps 240 and 360 may be performed based on the difference measure 590 and the metric vector. Also, the design correction steps 270 and 370 may be applied.

Figures 6 and 7 show two flow charts of a variant of the invention.

In the variant of Fig. 6, the calibration layout is used to obtain the measurement results for process I and the reference data of process II is used.

The difference correction step and the design correction step are applied in the same manner as described above.

In the variant of Fig. 7, a calibration layout is used to obtain the measurement results for Process I and Process II.

Thereafter, two different models may be calibrated for Process I and Process II, or existing calibration data may be reused and then metric vectors applied to the outputs of the calibration models of the two processes, instead of the measurement results, The difference modeling is calibrated from the results of the calibration of the model.

The disadvantage of this variant is that it requires calibration of three models. However, this may be more precise than the retargeting strategy of the prior art solution described in connection with Fig. It can also be less affected by the outliers that may appear when using the results directly at the measurement points.

Figure 8 shows three different layouts with measurement points.

A scanning electron microscope (SEM) can be used to measure CDs 810, 820, 830 that characterize portions 840, 850, 860 of the layout. More generally, a metrology tool can be used to measure parameters represented by characteristic dimensions of a portion of the layout, e.g., CD, space, or density. In this context, the CD is defined as the width of a portion of the design, and the space is defined as the width between two lines in a part of the design, vice versa depending on the tone of the resist. Density is a measure of the line against the total surface of the design.

The drawings to be described hereinafter illustrate a plurality of methods for performing the measurements. In addition, the same physical parameters define the metrics that can be used to model input parameters.

Figures 9a, 9b and 9c illustrate the use of space metrics with the layout of Figure 8.

The space metrics consider the density of the lines in the three different designs 810, 820, 830 of FIG. 810, a function is defined as the ratio of the intermediate surface 913a to the entire surface 910a of the disk with a diameter 912a tangent to the line, at a point 911a of the line of design. The observer at point 911a sees the outside of the line. The larger the ratio, the wider the space between the lines. Although the dimensions of the lines themselves are different from each other, the illustration of Figs. 9A, 9B and 9C has approximately 80% of the same space. Thus, it can be easily understood that the metric vector used only for the space will not accurately represent the design difference, and therefore two different processes are adapted to these differences.

Figures 10a, 10b and 10c illustrate the use of CD metrics with the layout of Figure 8.

The CD metric takes into account the density of the lines in the three different designs 810, 820, 830 of FIG. As an example of 810, a function is defined at the point 1011a of the line of design, the ratio of the surface 1013a in line to the entire surface 1010a of the disk with a diameter 1012a tangent to the line. An observer at point 1011a sees the inside of the line. The larger the ratio, the wider the line. 10A, 10B, and 10C have 80%, 60%, and 60% CD, respectively. Thus adding this second dimension to the metric vector will improve the design difference captured by the metric vector.

Figures 11A, 11B and 11C illustrate the use of density metrics with the layout of Figure 8.

The CD metric takes into account the density of the lines in the three different designs 810, 820, 830 of FIG. For example, at point 1111a of the line of design, the surface 1111a of the line in this section of the design for the total surface 1110a of the disc with diameter 1112a intersecting the line of this section of the design, ), The function is defined. An observer at point 1111a looks around the section of the design. The larger the ratio, the larger the density. 11A, 11B and 11C have a density of 50%, 50% and 30%, respectively. Thus adding this third dimension to the metric vector will improve the design difference captured by the metric vector.

The space metrics shown by the figures 910a, 910b, and 910c are the same for the layout sections 810, 820, and 830 of FIG. By adding the CD metric, the layout section 810 and the layout sections 820 and 830 can be distinguished from each other. By adding the density metric thereafter, it becomes possible to distinguish the layout sections 810 and 820 from the layout section 830.

In practice, CD, space and density are the most frequently used input variables to characterize the process so that representative models can be calibrated.

Among possible representations of the state variables of the target design that are observed during the process, the use of the geometry of the "kernel " provides some advantages because it can be used to define with respect to a set of patterns.

- Surface between the patterns in the set seen within the observation range from the point of interest outside the pattern - this surface can be represented as an expression of the external density of the design, and can be expressed as a ratio of the resist threshold to the resist threshold used to define the space metric Can be measured by one of the dimensions of < RTI ID = 0.0 >

- An inner surface of the pattern in the set viewed within the observation range from the point of interest inside the pattern-this surface may appear as an expression of the inner density of the design and may be represented by a ratio to the resist threshold for defining the CD metric, Can be measured by one of the dimensions (or vice versa)

The method of calculating the metric is disclosed in Park (J.-G. Park, S.-W. Kim, S.-B. Shim, S.-S. Suh, and H.-K. Oh (2011), 'The effective etch process proximity correction methodology for improving on-chip CD variation in 20 nm node DRAM gate ', Design for Manufacturability though Design-Process Integration V, proc. SPIE vol 7974).

This document also discloses a variation on the aforementioned kernel metric, wherein the field of view is defined by a sector. By means of this field of view, the definition of the outer intersection and the inner intersection can determine the space and CD metrics, respectively.

In this variation, angle? Is defined as a parameter of the kernel. For example, the metric can be calculated by the following formula:

At this time:

K (r) is the Gaussian kernel,

는 타깃 설계의 표면이고,

Is the surface of the target design,

A (θ) is the deformation modulus of the kernel by the angle θ.

Within the scope of the present invention, other variations of the kernel model can be computed to improve the accuracy of the determination of the process metrics.

Particularly preferred variants are described in European Patent Application No. EP 14305834.5, filed on even date herewith by the same applicant as the present application.

 In particular, the use of convolution for the field of view of a design by combining a kernel function and a deformation function is disclosed, and the deformation function is dependent on the viewing angle and the angle of incidence. The use of a convolution function greatly alleviates the computational load.

The method of the present invention can be used in many cases where process matching using differential models such as the following may be of interest.

- E-beam direct writing or optical projection lithography on semiconductor wafers: The method of the present invention can be used to absorb manufacturing variations such as different resists or new machines and can provide the same results as existing processes on wafers.

- Mask Write: The method of the present invention can be used to absorb changes in the mask write flow, provide the same print mask from different flows, and consider the wafer effect in the mask write step by applying the variant of FIG. It is possible to do.

- Inspection: Sometimes, it is more important than certain to be accurate when it comes to metrology standards, and different metrology systems can be calibrated to provide even results by using the process matching of the present invention.

- Other steps of the semiconductor manufacturing process, such as etching, CMP annealing.

The proposed strategy can be applied to a dose-only or geometry-only matching algorithm, which means that the input layout for the process will have a dose or geometry suitable for matching other process or input data sets. In addition, the strategy is applied in a single step, as disclosed by Applicant's European Patent Application Publication No. EP2559054, in combination with dose and geometry matching algorithms.

To calibrate the difference model, the only required information is the difference between the two processes. It is not necessary to access the measurement results from the two processes for the standard flow of FIG.

Thus, since it is not necessary to create a model for each process, the process can be viewed as a "black box" where processes from different companies can be matched, while keeping the interior of the process reliable. have.

In addition, the generated difference model operates in both ways, which means that the same model can be used so that process 1 can match process 2 or process 2 can be matched to process 1.

In addition, since using two models (one for each process) produces two sets of associated errors, the error synthesized by using a single model can be reduced.

In all embodiments of the present invention, the flowcharts shown in Figures 2, 4, 6 and 7, Process I in the drawing may be a process that always produces the same target or output layout in an ideal or perfect process, i.

In the embodiment of FIG. 2, the measurement result I 250 is defined as the same error as 0 nm at all points in the target layout. The same is true for the embodiments of Figs. 6 and 7. Therefore, the measurement data is hypothetical.

In the embodiment of FIG. 4, the input data set of process I is also a data set with a null error where the metric is formed at every point as a metric of the target layout.

The advantage of using the present invention to compute the correction to be applied to the actual process to match the result of the reference ideal process is that the geometry correction to be applied to the input layout is directly determined at the output of the calculation. This differs from standard simulation methods commonly used to find optimal solutions within specified tolerances. In these solutions, it is necessary to transform the model used to determine the imprinted resist in the designated input layout, and to find the geometry correction to be applied to the latter to imprint the target layout on the resist. In practical terms, it is essential to apply the bootstrap method by calculating all the solutions until one is found in the tolerance, since these models can not generally be reversed. It is a computer-intensive, long and substantial process, and an ideal reference process is no longer needed when applying the present invention.

This also provides a displacement to which the method of the present invention will be applied at a specified point in the target contour, where CD, space and density metrics can be defined. This is in contrast to the conventional calculation by a simulation method in which the model calculates the dose to be applied to all points of the target contour even at the point where the metric is not defined.

The examples disclosed herein only describe some embodiments of the present invention. These examples do not in any way limit the scope of the invention as defined by the following claims.

Claims (23)

A method for determining, by a computer, an output vector comprising an output variable, said output vector defining a correction to be applied to a feature of a second process for fabricating a semiconductor integrated circuit,
Obtaining (250,330) a first series of values of an input vector for a first process for fabricating the same semiconductor integrated circuit at a first plurality of points of a first layout,
Obtaining (260, 340) a second series of values of a component of an input vector for a second process at one of a first plurality of points on a first layout and a second plurality of points on a second layout,
Determining (240, 350, 360) a value of a state vector comprising a state variable, the state vector representing a state of a difference between a first series of values of the input vector and a second series of values, and
Obtaining (270, 370) an output vector for a series of values of the state vector,
/ RTI > of the output vector. 2. The method of claim 1, wherein the first step is a virtual process, and wherein the virtual process generates the same output layout as the input layout. 3. The method of claim 1 or 2, wherein the output vector comprises at least one of an edge displacement, a dose modulation and a combination thereof as an output variable. 4. The method of any one of claims 1 to 3, wherein the input vector comprises at least one of a CD and a space of an input design of the integrated circuit as an input variable. 5. The method of any one of claims 1 to 4, wherein the first layout is a calibration layout. 6. The method according to any one of claims 1 to 5, wherein the first step is a reference process. 7. The method according to any one of claims 1 to 6, wherein a series of values of the state vector is computed at at least one of an interpolation procedure and an extrapolation procedure using the first and second series of values of the input vector, / RTI > 8. A method according to any one of claims 1 to 7, wherein the first state variable is selected based on a discriminant for a component of a parameter vector on an area of a value for which the first and second processes are to be used, Way. 9. The method of claim 8, wherein a second state variable is added to the first state variable to increase the combined discrimination power within a specified computational load budget. 10. The method of claim 9, wherein the state vector comprises a state variable representing at least one of CD, space and density. 11. The method of claim 10, further comprising: determining a circle in contact with a first edge of a portion of the design, determining a circle inside the circle, and determining a surface area of a portion of the circle included between the first edge of the portion of the design and the second edge of the portion of the design And calculating a state variable representing the CD, as a ratio of a surface area of a portion of the circle to a surface area of the circle, by calculating a state variable representing the CD. 12. The method of claim 10 or 11, further comprising: determining a circle on the outside of the first portion of the design facing the next second portion of the design, Determining a surface area of a portion of a circle to be included between edges and determining an output vector in which a state variable representing a space is calculated by calculating a state variable representing a space as a ratio of a surface area of a portion of the disk to a surface area of the disk Way. 13. A method according to any one of claims 10 to 12, wherein a circle covering a plurality of parts of the design is determined, a surface area of a part of the circle included in a part of the design is determined, Wherein the state variable representing the density is calculated by calculating a state variable representing the density as a ratio of surface area. 10. The method of claim 9, wherein the state vector comprises a state variable representing at least one of an outer density and an inner density. 15. The method of claim 14, wherein the external density is calculated by multiplying the convolution of the synthesis of the kernel function centered on the point of interest and the point of interest of the target design by the distortion function according to the viewing angle and the selected angle of departure, Wherein a shift angle is selected to look outside the target design. 15. The method of claim 14, wherein the internal density is calculated by multiplying the convolution of the synthesis of the kernel function centered on the point of interest and the point of interest of the target design by the distortion function according to the viewing angle and the selected angle of departure, Wherein a shift angle is selected to look inside the target design. 17. A method according to any one of claims 3 to 16, wherein the output variable is an edge displacement that is converted to a dose modulation using a transform function. 18. The method of claim 17, wherein the transform function is one of a hat function, a rectangular function, a triangular function, and a Gaussian function. 19. The method of claim 18, wherein the transform function is a hat function defined by a parameter W _h . The method of claim 19, wherein the parameter W _h is determined such that W _h ≥ Max (abs (ΔEdge)) and W _h ≤ minShapeDistance, where ΔEdge is the edge obtained from the first series of values and the second series of values (Edge) values, and ShapeDistance is measured on a target layout. 21. The method according to claim 20, wherein a value Th of a percentage of the resist threshold is calculated using the formula Th = 0.5-DeltaEdge / Wh. CLAIMS 1. A computer program for determining a series of corrections to be applied to a second parameter of a second process for enhancing a semiconductor integrated circuit,
Computer code instructions for obtaining a first set of values of an input vector for a first process for fabricating the same semiconductor integrated circuit at a first plurality of points of a first layout,
Computer code instructions for obtaining a second series of values of a component of an input vector for a second process at one of a first plurality of points on a first layout and a second plurality of points on a second layout,
A computer code instruction for determining a value of a state vector comprising a state variable, the state vector representing a state of a difference between a first series of values of the input vector and a second series of values,
A computer code instruction for obtaining an output vector for a series of values of a state vector,
And a computer program. 23. A semiconductor manufacturing equipment configured to use an output of a computer program according to claim 22, wherein the semiconductor manufacturing equipment is adapted for direct writing onto a semiconductor wafer, writing on a mask plate, etching, chemical or mechanical planarization, baking of a semiconductor wafer, Annealing, and inspection of a mask or semiconductor surface.

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